A Model to Identify the Dimensions of Mobile Service Quality

Stiakakis, Emmanouil; Georgiadis, Christos K.

doi:10.1109/icmb.2011.43

Cited by 17 publications

(21 citation statements)

References 30 publications

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“…The above parameters can be linked to the model proposed by Stiakakis and Georgiadis (2011) on m-service quality parameters.…”

Section: Methodsmentioning

confidence: 99%

“…Chae, Kim, Kim and Ryu (2002) provided connection quality, content quality, interaction quality and contextual quality as the dimensions of m-service quality. However, Stiakakis and Georgiadis (2011) suggest that these only focus on information quality, rather than service quality. Lim, Widdows and Park (2006) identified five dimensions of perceived quality of m-services, namely, pricing plans, network quality, data services, billing system and customer service.…”

Section: Relationship Between Mobile and Electronic Governancementioning

confidence: 99%

“…Lu, Zhang and Wang (2009) proposed the three dimensions of mobile service quality as interaction quality, environment quality and outcome quality. Stiakakis and Georgiadis (2011) therefore suggest the following parameters of mobile service quality, namely, interaction quality-expertise, problem solving, information, security/privacy and customization/personalization; environment quality-equipment, design and context; and outcome quality-reliability, tangibles and valence. Here, service quality parameters have been identified for e-government (i.e., Internet and personal computer based).…”

Section: Relationship Between Mobile and Electronic Governancementioning

confidence: 99%

See 2 more Smart Citations

Service Quality Parameters for Mobile Government Services in India

Chanana¹,

Agrawal

Punia

2016

Global Business Review

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Information and communications technology (ICT)-based government service delivery in India is rapidly achieving a stage of maturity. With the increasing teledensity and the penetration of mobile devices, the Indian central and state governments have started to offer government services over mobile devices. As more and more government services are offered over mobile phones, it is important to gain an understanding of parameters determining the quality of mobile government services. The identification of service quality parameters will help stakeholders appropriately prioritize and position mobile-based government service delivery. This article presents the findings of an exploratory study using an online survey of Indian e-government experts on the service quality parameters for m-government in India. The study aims to identify and prioritize the service quality parameters based on similar parameters identified by researchers for e-government and mobile service quality.

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“…The above parameters can be linked to the model proposed by Stiakakis and Georgiadis (2011) on m-service quality parameters.…”

Section: Methodsmentioning

confidence: 99%

Section: Relationship Between Mobile and Electronic Governancementioning

confidence: 99%

Section: Relationship Between Mobile and Electronic Governancementioning

confidence: 99%

See 1 more Smart Citation

Service Quality Parameters for Mobile Government Services in India

Chanana¹,

Agrawal

Punia

2016

Global Business Review

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“…Through the expert review, valence [13,35] is not compatible to be listed under dialogue because this component was not directly showing the communication between company and customer but more to focus only towards customer impression. Valence is discarded to be listed under dialog because valence only involved customers' impressions that want to have good experience with the service compared to dialogue that insisted that both sides (company-customer) should interact with each other, therefore, it is shown clearly that there is no dialogue element in valence as it only involved one side and there is no interaction process happened .…”

Section: Risk Assessmentmentioning

confidence: 99%

The use of expert review in component development for customer satisfaction towards e-hailing

Idros

Mohamed

Jenal

2020

IJEECS

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The emergence of e-hailing apps has increased the demand of customers because online transportation service is very convenient in this modern society. As e-hailing provides an online platform for booking a ride, this apps also functions to connect the customer and driver, while at the same time allowing the customers to interact with customer service that company has provided to keep track of the satisfaction. Competition among e-hailing companies has increased since customers nowadays are very influential and knowledgeable in terms of choosing any transportation services that they want. The purpose of this study is to identify customer satisfaction towards e-hailing by embedding value co-creation model. Value co-creation is one of the concepts in Service Science that has been proved to increase customer satisfaction. Value co-creation is focused on company-customer interaction that helps in maintaining a good customer relationship and improve the company’s performance. Expert identification and evaluation procedure are used as a technique to adapt the definition of value co-creation model towards e-hailing. Then, the other factor from previous studies will be proposed as a component to be listed under value co-creation model and reviewed by an expert.

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“…To the best of the author's knowledge, these scales have not been examined and validated extensively in Malaysia. This model is a contemporary approach which could define service quality in the mobile context (Stiakakis & Georgiadis, 2011). In this particular model, service quality is divided into three main dimensions: interaction quality, environmental quality, and outcome quality.…”

Section: Mobile Service Qualitymentioning

confidence: 99%

The Mediating Role of Commitment in The Relationship Between Mobile Service Quality and Mobile Shopping Customer Loyalty in Malaysia

Dharaman¹,

Razak²

2020

J ENTREP BUS

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Online shopping is becoming increasingly important in the current era, rendering comprehension of consumer online shopping habits crucial. This notion rings true in the context of users and companies alike, thereby emerging as a big concern for e-commerce managers and researchers. One may assume that only by understanding the factors influencing consumer buying intentions for fashion items online will companies be better-positioned for meeting consumer needs. In this analysis, the relationship between customer online purchasing intentions and selected factors was investigated, specifically consumer innovativeness, fashion innovativeness, and fashion involvement. Quantitative research was implemented in the process, involving fashion online shoppers in Malaysia as the respondents after being selected via quota sampling from the ten most popular fashion shopping websites in Malaysia. The statistical method of Partial Least Square – Structural Equation Modelling (PLS-SEM) was then employed for the proposed model testing. The findings subsequently revealed the positive effects of consumer innovativeness, and fashion involvement on online purchase intention, whereas any significant relationship between the variable with fashion innovativeness was absent. However, this analysis was conducted in Malaysia; therefore, the results could be different if tested in other countries. Hence, similar studies related to fashion online purchase intention should be replicated in other Asian countries in the future.

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A Model to Identify the Dimensions of Mobile Service Quality

Cited by 17 publications

References 30 publications

Service Quality Parameters for Mobile Government Services in India

Service Quality Parameters for Mobile Government Services in India

The use of expert review in component development for customer satisfaction towards e-hailing

The Mediating Role of Commitment in The Relationship Between Mobile Service Quality and Mobile Shopping Customer Loyalty in Malaysia

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